on004122
BCIT Speed Control
EEG
…wheel and brake / foot pedals (Real Time Technologies; Dearborn, MI); Video Refresh…
- Participants
- 32
- Channels
- 64 (10-10)
- HED
- v8.0.0
- Size
- 36.2 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
Discover datasets
100 results for "real-time brain imaging" · page 10 of 10 · ranked by relevance
-
- nm000106
FRL Handwriting: Handwriting Decoding from Surface Electromyography
EMG…T.R., & CTRL-labs at Reality Labs. (2025). A generic non-invasive…
- Participants
- 100
- Size
- 45.3 GB
- Version
- v2.0.0
- Updated
- Jul 10, 2026
- nm000166
M3CV: Multi-subject, Multi-session, Multi-task EEG Database
EEG64-ch EEG, 95 subjects, 2 sessions, 6 paradigms (13 tasks). BrainAmp 250Hz Easycap 64-ch. DOI:10.1016/j.neuroimage.2022.119666
- Participants
- 95
- Channels
- 64 (10-10)
- Citations
- 25
- Size
- 21.6 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- nm000341
Cattan, Rodrigues & Congedo 2019 — Passive Head-Mounted Display Music-Listening EEG dataset (PHMD)
EEG…EEG-BIDS, an extension to the brain imaging data structure for electroencephalography…
- Participants
- 12
- Channels
- 16 (10-10)
- Citations
- 19
- HED
- v8.4.0
- Size
- 231 MB
- Version
- v1.0.1
- Updated
- Jul 10, 2026
- nm000277
Mainsah et al. 2025 — bigP3BCI: An Open, Diverse and Machine Learning Ready P300-based Brain-Computer Interface Dataset (Study G)
EEGBigP3BCI Study G is a P300-based brain-computer interface dataset comprising EEG recordings from 20 healthy subjects performing a 9x8 checkerboard visual speller task. This derivative dataset is Study G of 20 studies in the larger BigP3BCI collection, the largest public P300 BCI dataset with ~267 subjects total. The data were acquired at 256 Hz using 16-channel EEG with a g.USBamp amplifier and include target and non-target event classifications suitable for machine learning applications.
- Participants
- 20
- Channels
- 16 (10-10)
- HED
- v8.4.0
- Size
- 327 MB
- Version
- v1.0.1
- Updated
- Jul 10, 2026
- on006437
LIGHT Hypnotherapy
EEG…pursuit of meaning and self realization. 2 weeks before the first session…
- Participants
- 9
- Channels
- 64 (10-10)
- Size
- 4.31 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- nm000321
Mainsah et al. 2025 — bigP3BCI: An Open, Diverse and Machine Learning Ready P300-based Brain-Computer Interface Dataset (Study Q)
EEGBigP3BCI Study Q is a P300-based brain-computer interface dataset comprising EEG recordings from 36 ALS subjects across 3 sessions each, using a 6x6 color intensification speller paradigm. The dataset contains 32-channel EEG data sampled at 256 Hz with standardized 10-20 electrode montage, annotated with target and non-target event labels for machine learning applications. This derivative dataset is part of the larger BigP3BCI collection, the largest public P300 BCI dataset with recordings from approximately 267 subjects across 20 studies.
- Participants
- 36
- Channels
- 32 (10-10)
- HED
- v8.4.0
- Size
- 1.09 GB
- Version
- v1.0.1
- Updated
- Jul 10, 2026
- nm000220
BEETL Competition 2021 Motor Imagery Dataset A — transfer learning benchmark
EEGBeetl2021-A is a preprocessed motor imagery EEG dataset from the BEETL Competition Task 2 (NeurIPS 2021), comprising data from 3 healthy subjects collected during an online racing game (Cybathlon2020IC). The dataset contains 63-channel EEG recordings at 500 Hz with four-class motor imagery tasks (rest, left hand, right hand, feet) and serves as a benchmark for evaluating transfer learning and domain adaptation methods across heterogeneous EEG datasets and subjects. This dataset is part of a larger competition focused on advancing transfer learning for subject independence and cross-dataset generalization in brain-computer interfacing.
- Participants
- 3
- Channels
- 63 (10-10)
- HED
- v8.4.0
- Size
- 216 MB
- Version
- v1.0.1
- Updated
- Jul 10, 2026
- on004123
BCIT Traffic Complexity
EEG…wheel and brake / foot pedals (Real Time Technologies; Dearborn, MI); Video Refresh…
- Participants
- 29
- Channels
- 64 (10-10)
- HED
- v8.0.0
- Size
- 17.5 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- on004105
BCIT Auditory Cueing
EEG…wheel and brake / foot pedals (Real Time Technologies; Dearborn, MI); Video Refresh…
- Participants
- 17
- Channels
- 64 (10-10)
- HED
- v8.0.0
- Size
- 20.4 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026